GitLab

* Update README.md

* Update README.txt

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix launch script.
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* add standalone mode

* add comments.

* add tests for sampling.

* fix.

* make the code to run the standalone mode

* fix

* fix

* fix readme.

* fix.

* fix test
Co-authored-by: Chao Ma <mctt90@gmail.com>

* run dist server in dgl.

* fix bugs.

* fix example.

* check environment variables and fix lint.

* fix lint

* Fix

* Fix

* Fix

* add HGT example

* Update README.md

* Update model.py

* Update train_acm.py

* Add comments
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* minibatch rgcn

* minibatch based rgcn

* remove ogb

* lint

* Add sparse emb

* Fix

* Fix
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* pinsage example that uses sparse embedding update

* add difference from paper

* graphsage inductive example

* fix

* neighbor sampler data loader first commit

* more commit

* nodedataloader

* fix

* update RGCN example

* update OGB

* fixes

* fix minibatch RGCN crashing with self loop

* reverting gatconv test code

* fix

* change to new solution that doesn't require tf dataloader

* fix

* lint

* fix

* fixes

* change doc

* fix docstring

* docstring fixes

* return seeds and input nodes from data loader

* fixes

* fix test

* fix windows build problem

* add pytorch wrapper

* fixes

* add pytorch wrapper

* add unit test

* add -1 support to sample_neighbors & fix docstrings

* docstring fix

* lint

* add minibatch rgcn evaluations
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Tong He <hetong007@gmail.com>

* fix.

* fix tests.

* fix

* add tests.

* fix.

* have default rank.

* add comment.

* fix test.

* remove check

* simplify code.

* add test.

* split data evenly.

* simplify the distributed training code.

* add comments.

* add comments.

* ogb-deepwalk

* ?

* ?

* remove pyg

* add train_dist.

* Fix sampling example.

* use distributed sampler.

* fix a bug in DistTensor.

* fix distributed training example.

* add graph partition.

* add command

* disable pytorch parallel.

* shutdown correctly.

* load diff graphs.

* add ip_config.txt.

* record timing for each step.

* use ogb

* add profiler.

* fix a bug.

* add train_dist.

* Fix sampling example.

* use distributed sampler.

* fix a bug in DistTensor.

* fix distributed training example.

* add graph partition.

* add command

* disable pytorch parallel.

* shutdown correctly.

* load diff graphs.

* add ip_config.txt.

* record timing for each step.

* use ogb

* add profiler.

* add Ips of the cluster.

* fix exit.

* support multiple clients.

* balance node types and edges.

* move code.

* remove run.sh

* Revert "support multiple clients."

* fix.

* update train_sampling.

* fix.

* fix

* remove run.sh

* update readme.

* update readme.

* use pytorch distributed.

* ensure all trainers run the same number of steps.

* Update README.md
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* ogb-deepwalk

* update readme

* update readme

* update readme

* update readme

* ogbl-ddi

* readme

* citation&ppa
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* ogb-deepwalk

* update readme

* update readme

* update readme

* update readme

* ogbl-ddi

* readme
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* ogb-deepwalk

* update readme

* update readme

* update readme

* update readme
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* commit patch

* commit patch

* pointnet basic

* fix data

* reorg

* reorg

* temp status

* remove validate set

* add partseg data and model

* partseg miou

* clean up

* fix loss

* network definition match paper

* fix

* fix miou

* update data format

* fix

* fix

* working pointnet ssg cls

* avoid some pytorch bug

* fix script

* update hyperparams

* add msg module

* try different dataset

* update new dataset info

* quick fix to subgraph

* fix speed

* update training

* update

* fix bs

* update docstring

* update

* update

* remove parallel reduction in fps

* switch to kernel fps, training is 30% faster
Co-authored-by: Ubuntu <ubuntu@ip-172-31-20-181.us-west-2.compute.internal>

* Add ogbn-product with GAT with GraphSAGE sampling

* Update Readme

* Add self loop

* update score

* Update score

* Fix

* Update

* upd
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-186.ec2.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Zihao Ye <expye@outlook.com>

Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Chao Ma <mctt90@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-52-181.ec2.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* Move LifeSci

* Remove doc

* deepwalk

* add docstr, etc.

* add tested version

* some doc

* some doc

* add sample and some docs, fix a bug

* update speed

* update speed

* docs
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Use new version of Cora

* Fix import

* sign model

* mini-batch GPU eval & set default hyper-parameters

* add readme for sign

* minor

* test

* profile

* opt

* Some fix

* upd

* upd

* Add multigpu training support for graphsage unsupervised

* Add share neg

* Fix

* Add profile

* turn on eval

* upd

* Fix

* performance opt
Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-103.ec2.internal>
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Co-authored-by: Ubuntu <ubuntu@ip-172-31-87-240.ec2.internal>

* another first commit

* test commit

* porting to nowplaying

* fixes

* more updates

* update readme

* add performance

* update

* switch to return_uv

* update result

* Update examples/pytorch/pinsage/process_nowplaying_rs.py
Co-authored-by: Xiagkun Hu <huxk_hit@qq.com>

* update with comments
Co-authored-by: Xiagkun Hu <huxk_hit@qq.com>

* stgcn_wave model

* fix readme

* rm data file

* split sensors2graph

* rm dead code

* fix README

* rename class

* rm seed & dead code

* Update README.md

* rm dead code & networkx

* add num_layer papram, make model structure adjustable

* fix

* add model structure controller string, make code easier to understand and make model strcture more flexible

* Update main.py

* Update model.py

* fix

* Update README.md
Co-authored-by: Ubuntu <ubuntu@ip-172-31-14-255.ap-northeast-1.compute.internal>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* Add an example for GATNE-T

* Update README.md

* Add links for datasets

* Update README.md with running results

* Update README.md

* Add comments

* Update main.py

* Remove node type name `user`
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* initial version from distributed training.

This is copied from multiprocessing training.

* modify for distributed training.

* it's runnable now.

* measure time in neighbor sampling.

* simplify neighbor sampling.

* fix a bug in distributed neighbor sampling.

* allow single-machine training.

* fix a bug.

* fix a bug.

* fix openmp.

* make some improvement.

* fix.

* add prepare in the sampler.

* prepare nodeflow async.

* fix a bug.

* get id.

* simplify the code.

* improve.

* fix partition.py

* fix the example.

* add more features.

* fix the example.

* allow one partition

* use distributed kvstore.

* do g2l map manually.

* fix commandline.

* a temp script to save reddit.

* fix pull_handler.

* add pytorch version.

* estimate the time for copying data.

* delete unused code.

* fix a bug.

* print id.

* fix a bug

* fix a bug

* fix a bug.

* remove redundent code.

* revert modify in sampler.

* fix temp script.

* remove pytorch version.

* fix.

* distributed training with pytorch.

* add distributed graph store.

* fix.

* add metis_partition_assignment.

* fix a few bugs in distributed graph store.

* fix test.

* fix bugs in distributed graph store.

* fix tests.

* remove code of defining DistGraphStore.

* fix partition.

* fix example.

* update run.sh.

* only read necessary node data.

* batching data fetch of multiple NodeFlows.

* simplify gcn.

* remove unnecessary code.

* use the new copy_from_kvstore.

* update training script.

* print time in graphsage.

* make distributed training runnable.

* use val_nid.

* fix train_sampling.

* add distributed training.

* add run.sh

* add more timing.

* fix a bug.

* save graph metadata when partition.

* create ndata and edata in distributed graph store.

* add timing in minibatch training of GraphSage.

* use pytorch distributed.

* add checks.

* fix a bug in global vs. local ids.

* remove fast pull

* fix a compile error.

* update and add new APIs.

* implement more methods in DistGraphStore.

* update more APIs.

* rename it to DistGraph.

* rename to DistTensor

* remove some unnecessary API.

* remove unnecessary files.

* revert changes in sampler.

* Revert "simplify gcn."

This reverts commit 0ed3a34ca714203a5b45240af71555d4227ce452.

* Revert "simplify neighbor sampling."

This reverts commit 551c72d20f05a029360ba97f312c7a7a578aacec.

* Revert "measure time in neighbor sampling."

This reverts commit 63ae80c7b402bb626e24acbbc8fdfe9fffd0bc64.

* Revert "add timing in minibatch training of GraphSage."

This reverts commit e59dc8957a414c7df5c316f51d78bce822bdef5e.

* Revert "fix train_sampling."

This reverts commit ea6aea9a4aabb8ba0ff63070aa51e7ca81536ad9.

* fix lint.

* add comments and small update.

* add more comments.

* add more unit tests and fix bugs.

* check the existence of shared-mem graph index.

* use new partitioned graph storage.

* fix bugs.

* print error in fast pull.

* fix lint

* fix a compile error.

* save absolute path after partitioning.

* small fixes in the example

* Revert "[kvstore] support any data type for init_data() (#1465)"

This reverts commit 87b6997b

.

* fix a bug.

* disable evaluation.

* Revert "Revert "[kvstore] support any data type for init_data() (#1465)""

This reverts commit f5b8039c6326eb73bad8287db3d30d93175e5bee.

* support set and init data.

* support set and init data.

* Revert "Revert "[kvstore] support any data type for init_data() (#1465)""

This reverts commit f5b8039c6326eb73bad8287db3d30d93175e5bee.

* fix bugs.

* fix unit test.

* move to dgl.distributed.

* fix lint.

* fix lint.

* remove local_nids.

* fix lint.

* fix test.

* remove train_dist.

* revert train_sampling.

* rename funcs.

* address comments.

* address comments.

Use NodeDataView/EdgeDataView to keep track of data.

* address comments.

* address comments.

* revert.

* save data with DGL serializer.

* use the right way of getting shape.

* fix lint.

* address comments.

* address comments.

* fix an error in mxnet.

* address comments.

* add edge_map.

* add more test and fix bugs.
Co-authored-by: Zheng <dzzhen@186590dc80ff.ant.amazon.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-6-131.us-east-2.compute.internal>
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* shared memory history for multi-gpu training

* reorg
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* unsupervised graphsage first commit

* fix

* disable remove_edges and still got 0.90 performance

* optimize edgeids with multimap

* change hyperparams

* update README
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* control variate first commit

* bug fixes

* split to single and multi GPU

* update readme

* bugfix

* bugfix

* remove push

* bugfix on multi gpu

* update README
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-38-40.ec2.internal>